Cardiotocogram Data Classification using Random Forest based Machine Learning Algorithm

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Cardiotocogram Data Classification using Random Forest based Machine Learning Algorithm

The Cardiotocography is the most broadly utilized technique in obstetrics practice to monitor fetal health condition. The foremost motive of monitoring is to detect the fetal hypoxia at early stage. This modality is also widely used to record fetal heart rate and uterine activity. The exact analysis...

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Bibliographic Details
Main Authors:	Molla, M. M. Imran, Jui, Julakha Jahan, Bari, Bifta Sama, Rashid, Mamunur, Hasan, Md Jahid
Format:	Conference or Workshop Item
Language:	English English
Published:	Springer Singapore 2020
Subjects:	QA Mathematics TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/27518/ http://umpir.ump.edu.my/id/eprint/27518/1/Cardiotocogram%20Data%20Classification%20using%20Random1.pdf http://umpir.ump.edu.my/id/eprint/27518/2/Cardiotocogram%20Data%20Classification%20using%20Random.pdf

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